Hands-On Artificial Intelligence on Amazon Web Services: Decrease the time to market for AI and ML applications with the power of AWS
bPerform cloud-based machine learning and deep learning using Amazon Web Services such as SageMaker, Lex, Comprehend, Translate, and Polly/b h4Key Features/h4 ulliExplore popular machine learning and deep learning services with their underlying algorithms /li liDiscover readily available artificial...
Gespeichert in:
1. Verfasser: | |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Birmingham
Packt Publishing Limited
2019
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Ausgabe: | 1 |
Schlagworte: | |
Zusammenfassung: | bPerform cloud-based machine learning and deep learning using Amazon Web Services such as SageMaker, Lex, Comprehend, Translate, and Polly/b h4Key Features/h4 ulliExplore popular machine learning and deep learning services with their underlying algorithms /li liDiscover readily available artificial intelligence(AI) APIs on AWS like Vision and Language Services /li liDesign robust architectures to enable experimentation, extensibility, and maintainability of AI apps/li/ul h4Book Description/h4 From data wrangling through to translating text, you can accomplish this and more with the artificial intelligence and machine learning services available on AWS. With this book, you'll work through hands-on exercises and learn to use these services to solve real-world problems. You'll even design, develop, monitor, and maintain machine and deep learning models on AWS. The book starts with an introduction to AI and its applications in different industries, along with an overview of AWS artificial intelligence and machine learning services. You'll then get to grips with detecting and translating text with Amazon Rekognition and Amazon Translate. The book will assist you in performing speech-to-text with Amazon Transcribe and Amazon Polly. Later, you'll discover the use of Amazon Comprehend for extracting information from text, and Amazon Lex for building voice chatbots. You will also understand the key capabilities of Amazon SageMaker such as wrangling big data, discovering topics in text collections, and classifying images. Finally, you'll cover sales forecasting with deep learning and autoregression, before exploring the importance of a feedback loop in machine learning. By the end of this book, you will have the skills you need to implement AI in AWS through hands-on exercises that cover all aspects of the ML model life cycle. h4What you will learn/h4 ulliGain useful insights into different machine and deep learning models /li liBuild and deploy robust deep learning systems to production /li liTrain machine and deep learning models with diverse infrastructure specifications /li liScale AI apps without dealing with the complexity of managing the underlying infrastructure /li liMonitor and Manage AI experiments efficiently /li liCreate AI apps using AWS pre-trained AI services/li/ul h4Who this book is for/h4 This book is for data scientists, machine learning developers, deep learning researchers, and artificial intelligence enthusiasts who want to harness the power of AWS to implement powerful artificial intelligence solutions. A basic understanding of machine learning concepts is expected |
Beschreibung: | 1 Online-Ressource (426 Seiten) |
ISBN: | 9781789531473 |
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520 | |a The book starts with an introduction to AI and its applications in different industries, along with an overview of AWS artificial intelligence and machine learning services. You'll then get to grips with detecting and translating text with Amazon Rekognition and Amazon Translate. The book will assist you in performing speech-to-text with Amazon Transcribe and Amazon Polly. Later, you'll discover the use of Amazon Comprehend for extracting information from text, and Amazon Lex for building voice chatbots. You will also understand the key capabilities of Amazon SageMaker such as wrangling big data, discovering topics in text collections, and classifying images. Finally, you'll cover sales forecasting with deep learning and autoregression, before exploring the importance of a feedback loop in machine learning. By the end of this book, you will have the skills you need to implement AI in AWS through hands-on exercises that cover all aspects of the ML model life cycle. | ||
520 | |a h4What you will learn/h4 ulliGain useful insights into different machine and deep learning models /li liBuild and deploy robust deep learning systems to production /li liTrain machine and deep learning models with diverse infrastructure specifications /li liScale AI apps without dealing with the complexity of managing the underlying infrastructure /li liMonitor and Manage AI experiments efficiently /li liCreate AI apps using AWS pre-trained AI services/li/ul h4Who this book is for/h4 This book is for data scientists, machine learning developers, deep learning researchers, and artificial intelligence enthusiasts who want to harness the power of AWS to implement powerful artificial intelligence solutions. A basic understanding of machine learning concepts is expected | ||
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spelling | Tripuraneni, Subhashini Verfasser aut Hands-On Artificial Intelligence on Amazon Web Services Decrease the time to market for AI and ML applications with the power of AWS Tripuraneni, Subhashini 1 Birmingham Packt Publishing Limited 2019 1 Online-Ressource (426 Seiten) txt rdacontent c rdamedia cr rdacarrier bPerform cloud-based machine learning and deep learning using Amazon Web Services such as SageMaker, Lex, Comprehend, Translate, and Polly/b h4Key Features/h4 ulliExplore popular machine learning and deep learning services with their underlying algorithms /li liDiscover readily available artificial intelligence(AI) APIs on AWS like Vision and Language Services /li liDesign robust architectures to enable experimentation, extensibility, and maintainability of AI apps/li/ul h4Book Description/h4 From data wrangling through to translating text, you can accomplish this and more with the artificial intelligence and machine learning services available on AWS. With this book, you'll work through hands-on exercises and learn to use these services to solve real-world problems. You'll even design, develop, monitor, and maintain machine and deep learning models on AWS. The book starts with an introduction to AI and its applications in different industries, along with an overview of AWS artificial intelligence and machine learning services. You'll then get to grips with detecting and translating text with Amazon Rekognition and Amazon Translate. The book will assist you in performing speech-to-text with Amazon Transcribe and Amazon Polly. Later, you'll discover the use of Amazon Comprehend for extracting information from text, and Amazon Lex for building voice chatbots. You will also understand the key capabilities of Amazon SageMaker such as wrangling big data, discovering topics in text collections, and classifying images. Finally, you'll cover sales forecasting with deep learning and autoregression, before exploring the importance of a feedback loop in machine learning. By the end of this book, you will have the skills you need to implement AI in AWS through hands-on exercises that cover all aspects of the ML model life cycle. h4What you will learn/h4 ulliGain useful insights into different machine and deep learning models /li liBuild and deploy robust deep learning systems to production /li liTrain machine and deep learning models with diverse infrastructure specifications /li liScale AI apps without dealing with the complexity of managing the underlying infrastructure /li liMonitor and Manage AI experiments efficiently /li liCreate AI apps using AWS pre-trained AI services/li/ul h4Who this book is for/h4 This book is for data scientists, machine learning developers, deep learning researchers, and artificial intelligence enthusiasts who want to harness the power of AWS to implement powerful artificial intelligence solutions. A basic understanding of machine learning concepts is expected COMPUTERS / Systems Architecture / Distributed Systems & Computing COMPUTERS / Machine Theory Song, Charles Sonstige oth |
spellingShingle | Tripuraneni, Subhashini Hands-On Artificial Intelligence on Amazon Web Services Decrease the time to market for AI and ML applications with the power of AWS COMPUTERS / Systems Architecture / Distributed Systems & Computing COMPUTERS / Machine Theory |
title | Hands-On Artificial Intelligence on Amazon Web Services Decrease the time to market for AI and ML applications with the power of AWS |
title_auth | Hands-On Artificial Intelligence on Amazon Web Services Decrease the time to market for AI and ML applications with the power of AWS |
title_exact_search | Hands-On Artificial Intelligence on Amazon Web Services Decrease the time to market for AI and ML applications with the power of AWS |
title_exact_search_txtP | Hands-On Artificial Intelligence on Amazon Web Services Decrease the time to market for AI and ML applications with the power of AWS |
title_full | Hands-On Artificial Intelligence on Amazon Web Services Decrease the time to market for AI and ML applications with the power of AWS Tripuraneni, Subhashini |
title_fullStr | Hands-On Artificial Intelligence on Amazon Web Services Decrease the time to market for AI and ML applications with the power of AWS Tripuraneni, Subhashini |
title_full_unstemmed | Hands-On Artificial Intelligence on Amazon Web Services Decrease the time to market for AI and ML applications with the power of AWS Tripuraneni, Subhashini |
title_short | Hands-On Artificial Intelligence on Amazon Web Services |
title_sort | hands on artificial intelligence on amazon web services decrease the time to market for ai and ml applications with the power of aws |
title_sub | Decrease the time to market for AI and ML applications with the power of AWS |
topic | COMPUTERS / Systems Architecture / Distributed Systems & Computing COMPUTERS / Machine Theory |
topic_facet | COMPUTERS / Systems Architecture / Distributed Systems & Computing COMPUTERS / Machine Theory |
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